Half-Logistic Odd Power Generalized Weibull-inverse Lindley: Properties, Characterizations, Applications and Covid-19 Data

Q3 Mathematics
Arbër Qoshja, Artur Stringa, Klodiana Bani, Rea Spaho
{"title":"Half-Logistic Odd Power Generalized Weibull-inverse Lindley: Properties, Characterizations, Applications and Covid-19 Data","authors":"Arbër Qoshja, Artur Stringa, Klodiana Bani, Rea Spaho","doi":"10.37394/23206.2023.22.89","DOIUrl":null,"url":null,"abstract":"Using the Half-Logistic Odd Power Generalised Weibull-G family distributions, this article constructed a novel distribution termed the Half-Logistic Odd Power Generalised Weibull-inverse Lindley. Some of its statistical features are derived by us. Selecting the most efficient estimators is among the basic issues in parameter estimation theory. We are employing maximum likelihood estimation, moment estimation, least squares estimation, weighted least estimation, L-moment estimation, Maximum Product Spacing estimation, and techniques of minimum distances for the parameter estimation for the distribution. We will examine simulation research that compares the various estimators' levels of efficiency using the Kolmogorov-Smirnov test. Lastly, an analysis is done on an actual COVID-19 data set to demonstrate the adaptability of our suggested model in comparison to the fit obtained by several other competing distributions.","PeriodicalId":55878,"journal":{"name":"WSEAS Transactions on Mathematics","volume":"137 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"WSEAS Transactions on Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37394/23206.2023.22.89","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0

Abstract

Using the Half-Logistic Odd Power Generalised Weibull-G family distributions, this article constructed a novel distribution termed the Half-Logistic Odd Power Generalised Weibull-inverse Lindley. Some of its statistical features are derived by us. Selecting the most efficient estimators is among the basic issues in parameter estimation theory. We are employing maximum likelihood estimation, moment estimation, least squares estimation, weighted least estimation, L-moment estimation, Maximum Product Spacing estimation, and techniques of minimum distances for the parameter estimation for the distribution. We will examine simulation research that compares the various estimators' levels of efficiency using the Kolmogorov-Smirnov test. Lastly, an analysis is done on an actual COVID-19 data set to demonstrate the adaptability of our suggested model in comparison to the fit obtained by several other competing distributions.
半逻辑奇幂广义Weibull-inverse Lindley:性质、表征、应用和covid数据
利用半logistic奇幂广义Weibull-G族分布,构造了一个半logistic奇幂广义weibull -逆Lindley分布。它的一些统计特征是我们推导出来的。选取最有效的估计量是参数估计理论的基本问题之一。我们采用极大似然估计、矩估计、最小二乘估计、加权最小估计、l -矩估计、最大乘积间距估计和最小距离技术对分布进行参数估计。我们将研究使用Kolmogorov-Smirnov测试比较各种估计器效率水平的模拟研究。最后,对实际的COVID-19数据集进行了分析,以证明与其他几个竞争分布获得的拟合相比,我们建议的模型具有适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
WSEAS Transactions on Mathematics
WSEAS Transactions on Mathematics Mathematics-Discrete Mathematics and Combinatorics
CiteScore
1.30
自引率
0.00%
发文量
93
期刊介绍: WSEAS Transactions on Mathematics publishes original research papers relating to applied and theoretical mathematics. We aim to bring important work to a wide international audience and therefore only publish papers of exceptional scientific value that advance our understanding of these particular areas. The research presented must transcend the limits of case studies, while both experimental and theoretical studies are accepted. It is a multi-disciplinary journal and therefore its content mirrors the diverse interests and approaches of scholars involved with linear algebra, numerical analysis, differential equations, statistics and related areas. We also welcome scholarly contributions from officials with government agencies, international agencies, and non-governmental organizations.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信